Siddhisanket Raskar

Computer Scientist

Argonne Leadership Computing Facility
Argonne National Laboratory, IL, USA
sraskar@udel.edu

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Siddhisanket (Sid) Raskar

I am a Assistant Computer Scientist in the AI/ML group at Argonne National Laboratory. I work on AI architectures for scientific machine learning and on the design of next-generation AI architectures for science. My recent work involves performance benchmarking, modeling, and optimizations targeting modern ML workloads (e.g LLM, LMM, CNN, GNN, etc.) for heterogeneous and parallel architectures (e.g., GPUs and AI accelerators).

I obtained my Ph.D. under the guidance of Guang R. Gao on the topic of "Dataflow Software Pipelining” at the University of Delaware. I also have a Master’s in Computer Science from the University of Delaware and a Bachelor’s in Computer Engineering from the University of Pune, India.

My research interesrts are at the intersection of Machine Learning, High Performance Computing and Computer Architectures.

Research Interests :

• Machine Learning and AI Architectures
• High-Performance Computing
• Computing and Dataflow Models
• Computer Architecture and Systems
• Compilers Technology and Runtime Systems

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Professional Service

• Vice Chair Active member and Vice Chair for IEEE Computer Society Technical Community on Parallel Model and System: DataFlow and Beyond (DFSTC)
• Organizer:
  • Democratizing AI Accelerators for HPC Applications: Challenges, Success, and Support Birds of a Feather Session, SuperComputing 2024. [Website]
  • Programming AI Accelerators for Scientific Computing, Tutorial at Supercomputing 2024, Atlanta, USA. [GitHub]
  • Programming AI Accelerators for Scientific Computing, Tutorial at Supercomputing 2023, Denver, USA. [GitHub]
  • Programming AI Accelerators for Scientific Computing, Tutorial at Supercomputing 2022, Dallas, USA. [GitHub]
• Technical Reviewer EDAS'14, IPDPS’14, ASPLOS'15, DFM’15, CGO'15, ESPM'15 CGO’16, ESPM2’16, ASPLOS’16 ESPM2’18, ICS'18, DFM'19, CCGrid'20, ISC'20, BID'22, MLBench'23, SC'23, HiPC'23, CARLA'23, ICCD'23, Micro'23
• Program Committee BID'22, NPC'22, MLBench'23, HiPC'23, CARLA'23, ICS'24, CARLA'24, ATPESC'24, SC'24
• Session Chair PMAM'23
• Webmaster Postdoctoral Society of Argonne 2021,2022.
• Student Volunteer Supercomputing Conference. 2017,2019,2020.

Selected Talks

• LLM Inference Optimizations [Slides] [GitHub]
  ALCF HPC Hands-on Workshop 2024.
• AI Testbeds Deep Dive and Hands-on [Slides] [GitHub]
  ALCF HPC Hands-on Workshop 2024.
• Intro to AI Series: AI Accelerators [Slides] [Video] [GitHub]
  Introduction to AI-driven Science on Supercomputers 2024.
• Programming Novel AI Accelerators for Scientific Computing [Video]
  The University of Michigan Summer School (SciFM 2024).
• Introduction of AI-testbed and hands-on [Slides]
  Argonne Training Program on Extreme-Scale Computing (ATPESC 2023).
• Introduction on DataFlow Architectures and Trends [Slides]
  Argonne Training Program on Extreme-Scale Computing (ATPESC 2023).
• Introduction of AI-testbed and hands-on” [Slides] [Video]
  Argonne Training Program on Extreme-Scale Computing (ATPESC 2022).
• Overview of AI Testbeds at Argonne [Slides] [Video]
  2022 ALCF Simulation, Data, and Learning Workshop (SDL2022).
• Exploring OpenMP target offloading for the GraphCore architecture [Slides] [Video]
  Lightening talk at LLVM Developer's meeting 2022.
• A pathway to OpenMP In the GraphCore Architecture
  LDRD Expedition Day 2022.
• Overview of AI Testbeds at ANL [Video]
  ALCF Simulation, Data and Learning Workshop (SDL 2021).

Publications